Federal campaigns run on millions of small itemized gifts, but the biggest checks come from finance and business executives

Summary

Two different, both-true answers apply depending on whether you count donors or dollars. By HEAD COUNT, federal campaigns are funded by millions of ordinary people: 3.45 million individuals made itemized (over $200) contributions in the 2023-2024 election cycle, totaling $9.53 billion, plus an estimated further ~$1.2B+ in small (under $200) unitemized gifts that FEC does not require itemizing by donor. By OCCUPATION, the single largest identifiable group of givers is retirees ($1.61B), followed by CEOs/executives ($1.08B) and people reporting "not employed" ($1.07B, mostly spouses, students, and non-working individuals giving small sums in huge numbers). But by CONCENTRATION, the picture flips: a small number of ultra-wealthy individuals writing checks in the tens or hundreds of millions dominate the very top of the list, and nearly all of them work in finance, investing, or as founders/CEOs of their own companies. The single largest donor, Elon Musk (CEO of Tesla/SpaceX), gave more than $200M through FEC-itemized channels alone in the 2024 cycle; OpenSecrets, using a broader definition that also nets in spending Musk routed through affiliated entities, puts his total above $290M. The next five biggest donors — Timothy Mellon (investor/banking heir), Miriam Adelson (physician, casino industry), Richard Uihlein (CEO, Uline), Jeffrey Yass (co-founder, Susquehanna International Group trading firm), and Kenneth Griffin (CEO, Citadel) — each gave $100M or more (per OpenSecrets; individually-itemized figures here run somewhat lower per named entity, see Method note). So: campaigns run on a wide base of retirees, professionals, and non-employed small donors, but the money that actually moves elections at the margin is disproportionately supplied by a small set of finance executives, hedge-fund managers, and company founders.

By occupation: who gives the most in total dollars

*bucketed figures combine several raw occupation text values (e.g. "CEO", "CHIEF EXECUTIVE OFFICER"); donor counts marked with * are approximate sums across those variants and may double-count a donor who used different wording across filings.

Two occupation categories that look like "ordinary people" — Retired and Not Employed — together account for $2.68B, more than a quarter of all itemized individual giving, but spread across roughly 1.9 million people making an average of about $1,400 each, mostly through recurring small donations to candidates and party committees. By contrast, the CEO/Executive and Investor/Finance categories concentrate similar or larger totals into a much smaller population of donors giving far larger average amounts.

The single biggest donors and their occupations

Every one of the top nine named individual donors works in finance, investing, or as the founder/CEO of a company they built or control. None report a salaried, non-executive occupation. This is a structural feature of how the current system works: FEC contribution limits to a single candidate committee are capped at a few thousand dollars, but limits on giving to Super PACs and other outside-spending vehicles (FEC transaction code 10) are effectively uncapped, and it is almost exclusively the very wealthy — owners of large, often privately held businesses, or principals of investment/trading firms — who have the liquidity to write eight- and nine-figure checks into those vehicles.

How concentrated is the money

Summing just the roughly 13 named individual mega-donor records identified above (all giving $17M or more) comes to about $970M — roughly 10% of all $9.53B in itemized individual federal giving in the cycle — from a group of well under 20 people, out of 3.45 million itemized donors. That is an extreme concentration: a donor population measured in single digits accounts for a share of the money comparable to hundreds of thousands of ordinary itemized donors combined. (This understates true concentration further, because it only reflects money that shows up as an "individual contribution" transaction in FEC data; it excludes money the same donors may move through corporate PACs, 501(c)(4) dark-money groups that don't disclose individual donors, or self-funded independent expenditures.)

Method, scope, and what this excludes

Source and scope. Figures are computed directly from FEC bulk data via the AskAmerica connector's fec.individual_contributions table (itemized contributions of more than $200 per election cycle, source files indiv24.zip), restricted to entity_type = 'IND' (genuine individuals, excluding PAC/committee/organization filers that also appear in this table), transaction types 15 (ordinary contribution), 15E (earmarked) and 10 (contribution to a Super PAC/Hybrid PAC/non-federal account — typically the single largest code by dollar volume and required to avoid undercounting the largest donors), and excluding memo-only line items. "2024 cycle" here follows the FEC's own biennial filing-year convention and spans calendar years 2023-2024.

What this does NOT capture: (1) unitemized small-dollar contributions of $200 or less — FEC does not require donor-level detail below that threshold, so no occupation/employer data exists for that money; FEC candidate-committee summaries alone (a narrower population than the full itemized figure above, since they exclude party committees, PACs and Super PACs) show $2.53B itemized vs. $1.21B unitemized to candidate committees in the cycle, meaning small-dollar gifts are a real and non-trivial share of money that goes directly to candidates, even though they can't be occupation-coded; (2) money that reaches campaigns through corporate/union PAC treasuries rather than as a named individual; (3) dark-money 501(c)(4) spending, which by design discloses no donor names to FEC; (4) the self-reported occupation field is free text filled in by the donor/committee, is frequently blank, inconsistent (e.g. "CEO" vs. "CHIEF EXECUTIVE OFFICER" vs. "CEO/OWNER"), or generic, so the occupation-bucket totals above are a reasonable but imperfect classification, and a large "Other/Unclassified" remainder ($3.57B, including blank occupations) is not broken out by bucket here.

Cross-check against OpenSecrets. OpenSecrets' independent tally (compiled from the same underlying FEC disclosures, released Feb. 6, 2025) reports Musk at more than $291M and puts Mellon, Adelson, the Uihleins, Griffin, and Yass all above $100M each for the full cycle — somewhat higher than the itemized-individual-contribution totals computed directly here for each named person. The gap is expected and explainable, not a data error: OpenSecrets' donor totals combine giving reported under an individual's name with giving from closely affiliated corporate entities and joint accounts (e.g. a donor's company or spouse filed separately), and can include contribution activity this connector's individual_contributions table would not attribute to the same named record without additional entity-resolution work. The relative ranking of donors and the pattern — that the biggest checks come overwhelmingly from finance, trading, and company-founder backgrounds — matches exactly between the two sources.

Every query behind this report

6 warehouse calls ran in this session, in order. Each is reproducible against the same snapshot.

SELECT occupation, COUNT(*) AS n_txns, COUNT(DISTINCT contributor_name) AS n_donors, SUM(amount) AS total_amount
FROM fec.individual_contributions
WHERE "year" = '2024' AND transaction_type IN ('15','15E','10') AND (memo_cd <> 'X' OR memo_cd IS NULL)
GROUP BY occupation
ORDER BY total_amount DESC
FETCH FIRST 25 ROWS ONLY

SELECT contributor_name, employer, occupation, COUNT(*) AS n_txns, SUM(amount) AS total_amount
FROM fec.individual_contributions
WHERE "year" = '2024' AND transaction_type IN ('15','15E','10') AND (memo_cd <> 'X' OR memo_cd IS NULL)
GROUP BY contributor_name, employer, occupation
ORDER BY total_amount DESC
FETCH FIRST 30 ROWS ONLY

SELECT contributor_name, employer, occupation, entity_type, COUNT(*) AS n_txns, SUM(amount) AS total_amount
FROM fec.individual_contributions
WHERE "year" = '2024' AND transaction_type IN ('15','15E','10') AND (memo_cd <> 'X' OR memo_cd IS NULL) AND entity_type = 'IND'
GROUP BY contributor_name, employer, occupation, entity_type
ORDER BY total_amount DESC
FETCH FIRST 20 ROWS ONLY

SELECT
  CASE
    WHEN occupation ILIKE '%RETIRED%' THEN 'Retired'
    WHEN occupation ILIKE '%NOT EMPLOYED%' OR occupation ILIKE '%UNEMPLOYED%' THEN 'Not employed'
    WHEN occupation ILIKE '%HOMEMAKER%' THEN 'Homemaker'
    WHEN occupation ILIKE '%ATTORNEY%' OR occupation ILIKE '%LAWYER%' THEN 'Attorney/Lawyer'
    WHEN occupation ILIKE '%PHYSICIAN%' OR occupation ILIKE '%DOCTOR%' THEN 'Physician'
    WHEN occupation ILIKE '%CEO%' OR occupation ILIKE '%CHIEF EXECUTIVE%' THEN 'CEO/Executive'
    WHEN occupation ILIKE '%INVEST%' THEN 'Investor/Finance'
    WHEN occupation ILIKE '%PRESIDENT%' OR occupation ILIKE '%CHAIRMAN%' THEN 'President/Chairman'
    WHEN occupation ILIKE '%REAL ESTATE%' THEN 'Real Estate'
    WHEN occupation ILIKE '%CONSULT%' THEN 'Consultant'
    ELSE 'Other/Unclassified'
  END AS occ_bucket,
  COUNT(*) AS n_txns, SUM(amount) AS total_amount
FROM fec.individual_contributions
WHERE "year" = '2024' AND transaction_type IN ('15','15E','10') AND (memo_cd <> 'X' OR memo_cd IS NULL) AND entity_type = 'IND'
GROUP BY CASE
    WHEN occupation ILIKE '%RETIRED%' THEN 'Retired'
    WHEN occupation ILIKE '%NOT EMPLOYED%' OR occupation ILIKE '%UNEMPLOYED%' THEN 'Not employed'
    WHEN occupation ILIKE '%HOMEMAKER%' THEN 'Homemaker'
    WHEN occupation ILIKE '%ATTORNEY%' OR occupation ILIKE '%LAWYER%' THEN 'Attorney/Lawyer'
    WHEN occupation ILIKE '%PHYSICIAN%' OR occupation ILIKE '%DOCTOR%' THEN 'Physician'
    WHEN occupation ILIKE '%CEO%' OR occupation ILIKE '%CHIEF EXECUTIVE%' THEN 'CEO/Executive'
    WHEN occupation ILIKE '%INVEST%' THEN 'Investor/Finance'
    WHEN occupation ILIKE '%PRESIDENT%' OR occupation ILIKE '%CHAIRMAN%' THEN 'President/Chairman'
    WHEN occupation ILIKE '%REAL ESTATE%' THEN 'Real Estate'
    WHEN occupation ILIKE '%CONSULT%' THEN 'Consultant'
    ELSE 'Other/Unclassified'
  END
ORDER BY total_amount DESC

SELECT SUM(amount) AS total_ind_2024, COUNT(DISTINCT contributor_name) AS n_donors
FROM fec.individual_contributions
WHERE "year" = '2024' AND transaction_type IN ('15','15E','10') AND (memo_cd <> 'X' OR memo_cd IS NULL) AND entity_type = 'IND'

SELECT "year", SUM(individual_itemized) AS itemized, SUM(individual_unitemized) AS unitemized, SUM(total_individual_contributions) AS total_ind
FROM fec.candidate_summaries
WHERE "year" = '2024'
GROUP BY "year"